Pr(e)-CRM: Supercharging Your E- Business CRM Strategy

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1 Pr(e)-CRM: Supercharging Your E- Business CRM Strategy Presented by: Michael MacKenzie Chairman, Chief Research Officer Michael Doucette President C!nvergZ LLC 98 Main Street, Suite 515, Tiburon CA Phone:

2 Managing The Customer Relationship Today s Only Valuable and Sustainable Asset "To make our client s relationships with their customers more: Efficient - By increasing the the probability that time spent with a customer will generate increased Lifetime Customer Value (LCV) Effective - Through increasing the revenue generated from customers by increasing trial, intensification and crossselling to maximize LCV Focused - By identifying strategies to maximize and enrich each individual customer s relationship with the brand

3 Why pr(e)-crm SM? "Leverage your investment in an expensive and elaborate Customer Data Warehouse and operational e-crm system by: Ensuring that you CRM efforts start off successful and productive load the CRM/Sales recommendation engine with personalized knowledge of customers before the first interaction.

4 Why pr(e)-crm SM? "Have you already deployed a CRM system and are wondering how much each customer is adding to the bottom line and what it is doing for your customer relationships? A set of quantifiable measures of Brand Equity and Use Intensity each with a direct impact on per-customer cost, revenue, and profit.

5 Managing The Customer Relationship Creating a rich and rewarding journey with your customers "Integrated process for managing marketing, sales and service activity: Evaluate potential value of new prospects As well as your current ones Strengthen existing relationships Decrease vulnerability among your current customers More profit with less risk A few loyal and intense customers yield most of the profit LCV = Expected value of brand equity and use intensity Maximizing LCV is the objective function driving CRM

6 Data Fusion is the Heart of Pr(e)-CRM Using All of the Available Data and Powerful Analytic CRM Tools "Pr(e)-CRM merges data from IT with proprietary Market Research Market Research provides traditional Usage & Attitude (U&A) Segmentation on demographics,values, attitudes, benefits sought, perception and use of category and competition Competitive perception and behaviour are essential to the calculation of total potential Lifetime Customer Value IT provides an integrated Customer Information File (CIF) and the granular transaction file Transaction file must be very detailed in product/service and also must retain granularity in the time series Only in this manner will the fusion with the U&A be built on solid and replicable bridge variables

7 Optimize Cross-Selling Strategy "Use knowledge of what a customer has bought, and just as important Who she is?, to determine what should be offered at each sales opportunity on the journey "Improve the odds of success in every selling opportunity # One to one marketing - Offering only the right products, services and messages to each customer means a much higher retention rate as well as better probability of selling # Virtuous circle - Improving the odds increases customer satisfaction and sales enthusiasm which further improves the odds # Most importantly - reduce price sensitivity and get better margins

8 Potential Market Potential Drives Relationships High High Potential Value/ Non-customers High Potential Value/ High Share of Customer LCV High Potential Value/ Low Share of Customer LCV Low Low Potential Value/ Low Share of Customer LCV Share of Customer LCV Low Potential Value/ High Share of Customer LCV High

9 Market Potential Drives Relationships Quadrant High Potential Value/ High Share of Customer LCV Maintain & Enhance Reward, build loyalty, bar competition from stealing your best customers!! High Potential Value/ Non-customers High Potential Value/ Low Share of Customer LCV Acquire & Convert Intensify & Cross-sell Invest to own this customer over their lifetime!! Educate, demonstrate value. Intensify and grow this customer!! Low Potential Value/ High Share of Customer LCV Sustain Lacks potential, sustain relationship, but no great loss!! Low Potential Value/ Low Share of Customer LCV Prune Poor potential, poor customer, encourage attrition, prune!!

10 Enhance Strategy with Insight "Past purchases and behavior are highly predictive of the future, but offer only partial guide to your customers needs and what is truly driving their behaviors # Demographics are important but psychographics are more predictive - People with similar income, race and age will seek vastly different experiences # Attitudes and preferences will manifest themselves in different contexts # Proprietary market research provides insight to drive relationship building

11 Enhance Strategy with Insight Very volatile, Can change very rapidly Behavior Attitudes & Preferences Based on attitudes and preferences Changes dramatically based on different life stages More volatile, Change quickly Based on values Influenced by advertising, marketing, peers Values Stable, Change very slowly Formed early Only changed by major life events

12 Enhance Strategy with Insight Behavior Attitudes & Preferences Values To change your customer s behavior you have to: understand their attitudes and preferences and their foundation values

13 Pr(e)CRM Intelligent Marketing Process Orders Metadata General Ledger Transactions Customer Service Back Office Transaction Systems Customer Data Warehouse Pr(e)CRM Process Front End e-crm Relationship Management System Pr(e)CRM provides the customer intelligence that glues your customer business intelligence systems to your tactical operational CRM system

14 A Case in Study Analytical CRM for a multi-brand multi-channel retailer "Brands span categories and economic strata Differentiated, but with huge overlap across categories and som across economic strata Products range from one-time consumables and services all the way into multi-generational durables "Channels include Retail Store, Catalog and Interne Most customers are multi-channel Most customers are identified and tied to the CIF at the time of sale "Near ideal situation for analytical CRM

15 A Case in Study Analytical CRM for a multi-brand multi-channel retailer "Sample customer data Classify customers by initial type and profitability Exploratory research with great customers to identify important dimensions of the brands "U&A survey with customers, competitive customers and new prospects Survey uses telephone/mail and telephone/on-line

16 A Case in Study Analytical CRM for a multi-brand multi-channel retailer "U&A study covers: Demographics structural lifecycle market shapers Psychographics basic values defining people in all realms of their life Attitudes beliefs about the category and it s use and fit in their lives Perceptions brand image of full competitive context Brand equity indices derive from correlation with use Use and purchase behaviour category and competitive use Evaluates all use and purchase context and situations Use intensity indices derive from analysis of brand, competitive and category use

17 A Case in Study Analytical CRM for a multi-brand multi-channel retailer "Data Fusion for Analysis: Highly granular transaction data merged with U&A Pattern analysis and business sense guides development of use intensity composite variables in the CIF and transaction files to be used explicitly in analysis of the U&A Composite variables are quite complex summaries of purchase behaviour of full range of products through time Variables can be complex because they will batch process offline and only the indices need be attached to the CIF The migration paths from prospect to one of the groups of high yield customers are the most powerful variables

18 A Case in Study Analytical CRM for a multi-brand multi-channel retailer "Pr(e)-CRM or Hot Rodded Analytical CRM: Many modeling and analytical techniques are used, but by far the most important is clustering into market segments Simultaneous on many different kinds of variables causes some digressions Massive amounts of missing data, the entire transaction file for the prospects and competitive buyers Powerful econometrical model estimates the brand equity and the LCV

19 A Case in Study Analytical CRM for a multi-brand multi-channel retailer "Executing on Pr(e)-CRM Immediately all customers are segmented and classified based on LCV Future business with customer from the past is more effective on day one Competitive and non-users have no transaction data Customers with no survey, have only transaction history Decision tree type (CHAID) model classifies customers with no survey, first with only variables from the transaction file Second we increase accuracy(80-90%) with a few(4-6) extra questions

20 A Case in Study Analytical CRM for a multi-brand multi-channel retailer "Every customer and prospect now has a planned strategy attached "The best customers have migration paths to take them to the highest yield and strongest relationship "Loyalty is based on added value "New brand opportunities identified "Isolated action against competitors, hit them only where the need to be hit, don t discount the gravy

21 Pr(e)-CRM "Pr(e)-CRM will: Identify your best customers: Differentiating between the proselytisers actively promoting the brand And those most vulnerable to competitive theft or category lapse Identify customers in need of pruning whose future lies elsewhere Identify your best prospects for: Share stealing investment activity New trial attracted into the category

22 Pr(e)-CRM "Pr(e)-CRM will: Identify the use intensity factors generating revenue and profit in the category: Total expenditures, share of income/expenditures Share of customer and category Share of potential use and/or consumption context Brand loyalty Use consistency

23 Pr(e)-CRM "Pr(e)-CRM will: Profile the customers on factors driving trial, share, and intensity behaviour Demographics are structural lifecycle market shapers Share of customer and category Psychographics are the basic values defining people in all realms of their life Attitudes are beliefs about the category and it s use Perceptions are the competitive brand imagery in the category Build a model linking these factors explicitly to use intensity and implicitly to bottom line performance In order derive from a profit maximizing objective function to drive all customer and prospect interaction in the long term best interest of brand and customer

24 Brand Equity is Based on LCV "Your brand s equity is the sum of all customers and prospects lifetime customer value "Brand equity and hence LCV is comprised of both: bottom line driven measures such as total revenue, share of customer, share of category, average sale per customer, average sale per transaction perceptual or more emotional measures such as the service, quality, trust, status, self-identification and other image dimensions relevant to that segment of that category

25 LCV = Expected Value of Use Intensity and Brand Equity Indices "The focus of customer relationship centric companies is maximizing the lifetime customer value of each and every customer and prospect "The heart of pr(e)-crm is an LCV objective function maximizing a quantifiable measure of LCV at each and every touch-point between brand and customer "We use a composite scale to create LCV in order to get a more accurate measure of the potential, rather than the realized, value

26 Is Your Organization Ready? "Can you company take advantage of ConvergZ leading edge pr(e)-crm process? Review the following checklist and assess your company s readiness to proceed. Has your organisation: 1. Completed an analytical CRM pilot project(s) 2. Implemented operational CRM system 3. Implemented a Customer Data Warehouse 4. Successfully developed an integrated Customer Information File (CIF) 5. Routinely deploys segmented marketing campaigns across multiple channels 6. Successfully differentiated your products or services 7. Organized your company around customer centric measures 8. High level executive sponsorship of relationship marketing, customer-centric sales and marketing, 1 to 1 marketing, automated marketing systems, CRM, mass customization, etc.

27 Conclusion "ConvergZ pr(e)-crm is innovative new way for companies to look at their customers By combining leading edge data mining and advanced analytical CRM techniques ConvergZ pr(e)-crm process will: super-charges your companies CRM efforts provides understanding of the fundamental customer relationships that lie at the heart of your business makes reliable estimates of the future economic value of your customers and prospects maximizes the intensity and value of your customer relationships and drives your brand equity to new levels 2001 ConvergZ LLC LLC - All rights reserved.

28 Questions and Answers "Questions?

29 Who We Are - Biographies Michael MacKenzie Michael MacKenzie has spent 20 years in Marketing and Public Opinion Research helping companies and organizations to better serve their constituencies. His approach has been to develop custom, quasiexperimental hybrid models combining the best of quantitative and qualitative methodologies. He passionately believes this is the best way to bring as much certainty as possible to decisions about human attitudes, perceptions, and behaviors. Founder and Chief Research Officer and Chairman of ConvergZ LLC. Former Chief Research Officer of a large international marketing and opinion research company.

30 Who We Are - Biographies Michael MacKenzie Michael s research and business experience includes: Founded four of Angus Reid s six offices in Canada Developed research methods which accounted for 60% ($20,000,000) of sales Developed proprietary simultaneous behavior and attitudinal segmentation techniques Product/ service feature and price simulation and optimization models Mentored the other 100 researchers on design and analysis. Developed unique proprietary Global Market Potential Model for estimating and managing brand equity across cultures Interactive geographic customer information files for managing customer relationships and exploiting cross-selling possibilities Invited speaker at several international conferences

31 Who We Are - Biographies Michael Doucette Michael s passion is for developing systems that help organizations answer complex problems. He has spent the last ten years working as a consultant and systems engineer for one of the premier business intelligence and data warehousing software vendors. Michael believes that information systems have to be driven by an organizations business needs and not technology for the sake of technology. Strong business vision enabled by technology and prudent project management are the recipe for a project s success. Founder and President of ConvergZ LLC Former consultant and systems engineer with large international business intelligence and data warehousing software vendor

32 Who We Are - Biographies Michael Doucette Michael s business and consulting experience includes: Developed Global Data Warehousing methodology for large international software company as part of Global Consulting Methodology Architecture effort Helped create Global Project Support office Worked with a wide variety of Fortune 1000 & FP500 clients providing business intelligence and data warehousing solutions including developing technical architectures and designing and data modeling dimension data warehouses Specialist in developing Information systems for solving complex business decision support, statistical, data mining, forecasting and econometric problems Over 10 years of market research experience Multivariate statistical and data analysis specialist Assisted in developing methodology for hybrid technology and labor market forecasting approach

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